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Algorithms for the graph coloring problem based on swarm intelligence

机译:基于群体智能的图着色问题算法

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In this paper, we tailor the Artificial Bee Colony (ABC) algorithm to solve the Graph Coloring Problem (GCP). We call this algorithm as the ABC-GCP. In the proposed ABC-GCP, a sequence of nodes of the given graph is generated. Then, based on this order of nodes, a color assignment algorithm is executed on the graph to color it. The sequence generation is implemented by the ABC algorithm in which a vector of continuous components is mapped to a sequence of integer numbers. The color assignment is based on a known heuristic called “Recursive Largest First (RLF)”, which gets the generated sequence and tries to color it with a least amount of colors. The proposed ABC-GCP is tested with randomly gated graphs with different densities, and it is compared with some other relevant algorithms. The experimental results demonstrate the superiority of the proposed algorithm in comparison with the other algorithms.
机译:在本文中,我们量身定制了人工蜂群(ABC)算法来解决图形着色问题(GCP)。我们将此算法称为ABC-GCP。在提出的ABC-GCP中,将生成给定图的一系列节点。然后,基于节点的此顺序,对图形执行颜色分配算法以对其进行着色。序列生成是通过ABC算法实现的,该算法将连续分量的矢量映射到整数序列。颜色分配基于一种称为“递归最大优先级(RLF)”的已知启发式方法,该方法获取生成的序列并尝试以最少的颜色对其进行着色。所提出的ABC-GCP使用具有不同密度的随机门控图进行了测试,并与其他一些相关算法进行了比较。实验结果证明了该算法与其他算法的优越性。

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